Untitled15.ipynb
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[21]:
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("universities.csv")
df
[21]:
| Univ | SAT | Top10 | Accept | SFRatio | Expenses | GradRate | |
|---|---|---|---|---|---|---|---|
| 0 | Brown | 1310 | 89 | 22 | 13 | 22704 | 94 |
| 1 | CalTech | 1415 | 100 | 25 | 6 | 63575 | 81 |
| 2 | CMU | 1260 | 62 | 59 | 9 | 25026 | 72 |
| 3 | Columbia | 1310 | 76 | 24 | 12 | 31510 | 88 |
| 4 | Cornell | 1280 | 83 | 33 | 13 | 21864 | 90 |
| 5 | Dartmouth | 1340 | 89 | 23 | 10 | 32162 | 95 |
| 6 | Duke | 1315 | 90 | 30 | 12 | 31585 | 95 |
| 7 | Georgetown | 1255 | 74 | 24 | 12 | 20126 | 92 |
| 8 | Harvard | 1400 | 91 | 14 | 11 | 39525 | 97 |
| 9 | JohnsHopkins | 1305 | 75 | 44 | 7 | 58691 | 87 |
| 10 | MIT | 1380 | 94 | 30 | 10 | 34870 | 91 |
| 11 | Northwestern | 1260 | 85 | 39 | 11 | 28052 | 89 |
| 12 | NotreDame | 1255 | 81 | 42 | 13 | 15122 | 94 |
| 13 | PennState | 1081 | 38 | 54 | 18 | 10185 | 80 |
| 14 | Princeton | 1375 | 91 | 14 | 8 | 30220 | 95 |
| 15 | Purdue | 1005 | 28 | 90 | 19 | 9066 | 69 |
| 16 | Stanford | 1360 | 90 | 20 | 12 | 36450 | 93 |
| 17 | TexasA&M | 1075 | 49 | 67 | 25 | 8704 | 67 |
| 18 | UCBerkeley | 1240 | 95 | 40 | 17 | 15140 | 78 |
| 19 | UChicago | 1290 | 75 | 50 | 13 | 38380 | 87 |
| 20 | UMichigan | 1180 | 65 | 68 | 16 | 15470 | 85 |
| 21 | UPenn | 1285 | 80 | 36 | 11 | 27553 | 90 |
| 22 | UVA | 1225 | 77 | 44 | 14 | 13349 | 92 |
| 23 | UWisconsin | 1085 | 40 | 69 | 15 | 11857 | 71 |
| 24 | Yale | 1375 | 95 | 19 | 11 | 43514 | 96 |
[23]:
s2 = [20,30,40,50,60,70,90,55,66,77,]
scores2 = pd.Series(s2)
print(scores2)
plt.figure(figsize=(6,2))
plt.title("Boxplot for batsman scores")
plt.xlabel("Scores")
plt.boxplot(scores2, vert = False)
0 20 1 30 2 40 3 50 4 60 5 70 6 90 7 55 8 66 9 77 dtype: int64
[23]:
{'whiskers': [<matplotlib.lines.Line2D at 0x1c99c620980>,
<matplotlib.lines.Line2D at 0x1c99c620cb0>],
'caps': [<matplotlib.lines.Line2D at 0x1c99c620f50>,
<matplotlib.lines.Line2D at 0x1c99c621250>],
'boxes': [<matplotlib.lines.Line2D at 0x1c99c620770>],
'medians': [<matplotlib.lines.Line2D at 0x1c99c621520>],
'fliers': [<matplotlib.lines.Line2D at 0x1c99c621820>],
'means': []}[ ]:
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